88 citations · 296 across the 16 of their papers we have counts for
16 papers
Merging multiple input descriptors and supervisors in a deep neural network for tractogram filtering
Daniel Jörgens, Pierre-Marc Jodoin, Maxime Descoteaux +1
One of the main issues of the current tractography methods is their high false-positive rate. Tractogram filtering is an option to remove false-positive streamlines from tractograp…
What Matters in Reinforcement Learning for Tractography
Antoine Théberge, Christian Desrosiers, Maxime Descoteaux +1
Recently, deep reinforcement learning (RL) has been proposed to learn the tractography procedure and train agents to reconstruct the structure of the white matter without manually…
FIESTA: Autoencoders for accurate fiber segmentation in tractography
Félix Dumais, Jon Haitz Legarreta, Carl Lemaire +7
White matter bundle segmentation is a cornerstone of modern tractography to study the brain's structural connectivity in domains such as neurological disorders, neurosurgery, and a…
Considerations and recommendations from the ISMRM Diffusion Study Group for preclinical diffusion MRI: Part 2 -- Ex vivo imaging: added value and acquisition
Kurt G Schilling, Francesco Grussu, Andrada Ianus +54
The value of preclinical diffusion MRI (dMRI) is substantial. While dMRI enables in vivo non-invasive characterization of tissue, ex vivo dMRI is increasingly used to probe tissue…
Considerations and Recommendations from the ISMRM Diffusion Study Group for preclinical diffusion MRI: Part 1 -- In vivo small-animal imaging
Ileana O Jelescu, Francesco Grussu, Andrada Ianus +54
Small-animal diffusion MRI (dMRI) has been used for methodological development and validation, characterizing the biological basis of diffusion phenomena, and comparative anatomy.…
Generative Sampling in Bundle Tractography using Autoencoders (GESTA)
Jon Haitz Legarreta, Laurent Petit, Pierre-Marc Jodoin +1
Current tractography methods use the local orientation information to propagate streamlines from seed locations. Many such seeds provide streamlines that stop prematurely or fail t…
Manifold-aware Synthesis of High-resolution Diffusion from Structural Imaging
Benoit Anctil-Robitaille, Antoine Théberge, Pierre-Marc Jodoin +3
The physical and clinical constraints surrounding diffusion-weighted imaging (DWI) often limit the spatial resolution of the produced images to voxels up to 8 times larger than tho…
Filtering in tractography using autoencoders (FINTA)
Jon Haitz Legarreta, Laurent Petit, François Rheault +4
Current brain white matter fiber tracking techniques show a number of problems, including: generating large proportions of streamlines that do not accurately describe the underlyin…
Medical Imaging with Deep Learning: MIDL 2020 -- Short Paper Track
Tal Arbel, Ismail Ben Ayed, Marleen de Bruijne +3
This compendium gathers all the accepted extended abstracts from the Third International Conference on Medical Imaging with Deep Learning (MIDL 2020), held in Montreal, Canada, 6-9…
Magic DIAMOND: Multi-Fascicle Diffusion Compartment Imaging with Tensor Distribution Modeling and Tensor-Valued Diffusion Encoding
A. Reymbaut, A. Valcourt Caron, G. Gilbert +5
Diffusion tensor imaging provides increased sensitivity to microstructural tissue changes compared to conventional anatomical imaging but also presents limited specificity. To tack…
Advanced encoding methods in diffusion MRI
Alexis Reymbaut, Maxime Descoteaux
Discovering a new field is not usually an easy process, especially when you choose magnetic resonance imaging (MRI). MRI is one of the few non-invasive medical procedures, if not t…
Tractography and machine learning: Current state and open challenges
Philippe Poulin, Daniel Jörgens, Pierre-Marc Jodoin +1
Supervised machine learning (ML) algorithms have recently been proposed as an alternative to traditional tractography methods in order to address some of their weaknesses. They can…
NODDI-SH: a computational efficient NODDI extension for fODF estimation in diffusion MRI
Mauro Zucchelli, Maxime Descoteaux, Gloria Menegaz
Diffusion Magnetic Resonance Imaging (DMRI) is the only non-invasive imaging technique which is able to detect the principal directions of water diffusion as well as neurites densi…
Nonparametric Bayes Models of Fiber Curves Connecting Brain Regions
Zhengwu Zhang, Maxime Descoteaux, David B. Dunson
In studying structural inter-connections in the human brain, it is common to first estimate fiber bundles connecting different regions of the brain relying on diffusion MRI. These…
Non Local Spatial and Angular Matching : Enabling higher spatial resolution diffusion MRI datasets through adaptive denoising
Samuel St-Jean, Pierrick Coupé, Maxime Descoteaux
Diffusion magnetic resonance imaging datasets suffer from low Signal-to-Noise Ratio, especially at high b-values. Acquiring data at high b-values contains relevant information and…
Local Water Diffusion Phenomenon Clustering From High Angular Resolution Diffusion Imaging (HARDI)
Romain Giot, Christophe Charrier, Maxime Descoteaux
The understanding of neurodegenerative diseases undoubtedly passes through the study of human brain white matter fiber tracts. To date, diffusion magnetic resonance imaging (dMRI)…